Skip to content

Commit

Permalink
Revert "corrections erreur Marthe"
Browse files Browse the repository at this point in the history 
This reverts commit 09d0588.
  • Loading branch information
@marthevienne
marthevienne committed Jan 7, 2025
1 parent 7091eba commit bfb25cc
Showing 1 changed file with 77 additions and 129 deletions.
206 changes: 77 additions & 129 deletions backend/bloom/tasks/create_update_excursions_segments.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -124,143 +124,91 @@ def run():
for vessel_id in batch["vessel_id"].unique():
df_end = batch.loc[batch["vessel_id"] == vessel_id].copy()
df_end.rename(columns={"timestamp": "timestamp_end",
"heading": "heading_at_end",
"speed": "speed_at_end",
"longitude": "end_longitude",
"latitude": "end_latitude"
}, inplace=True)
"heading": "heading_at_end",
"speed": "speed_at_end",
"longitude": "end_longitude",
"latitude": "end_latitude"
}, inplace=True)
df_end.sort_values("timestamp_end", inplace=True)
df_end.reset_index(drop=True, inplace=True)
# get every end entry but the last one ; each one of them will be the start point of a segment
if len(df_end)>1:
df_start = df_end.iloc[0:-1, :].copy()
for col in df_start.columns:
df_start.rename(columns={col: col.replace("end", "start")}, inplace=True)
vessel_last_segment = pd.DataFrame()
if last_segment.shape[0] > 0:
vessel_last_segment = last_segment.loc[
last_segment["vessel_id"] == vessel_id, ["mmsi", "timestamp_end", "heading_at_end", "speed_at_end",
"end_position", "excursion_id", "arrival_port_id"]]
vessel_last_segment["start_latitude"] = vessel_last_segment["end_position"].apply(lambda x: x.y)
vessel_last_segment["start_longitude"] = vessel_last_segment["end_position"].apply(lambda x: x.x)
vessel_last_segment.drop("end_position", inplace=True, axis=1)
vessel_last_segment.rename(columns={"timestamp_end": "timestamp_start",
"heading_at_end": "heading_at_start",
"speed_at_end": "speed_at_start",
}, inplace=True)
if vessel_last_segment.shape[0] > 0:
# if there's a last segment for this vessel, then it's not the first time a position for this vessel is received
is_new_vessel = False
# and it becomes the start point of the first new segment
df_start.loc[-1] = vessel_last_segment.iloc[0]
df_start.sort_index(inplace=True)
df_start.reset_index(drop=True, inplace=True)
# checks if the excursion of the last segment is closed or not
if vessel_last_segment["arrival_port_id"].iloc[0] >= 0:
open_ongoing_excursion = False
else:
open_ongoing_excursion = True
ongoing_excursion_id = int(vessel_last_segment["excursion_id"].iloc[0])

else:
# if there's no last segment for this vessel, then it's the first time a position for this vessel is received
is_new_vessel = True
# so we duplicate the starting point to have the first segment while setting it up 1s behind in time (so timestamp_start != timestamp_end)
df_start.loc[-1] = df_start.loc[0]
df_start["timestamp_start"].iloc[-1] += timedelta(0, -1)
df_start.sort_index(inplace=True)
df_start.reset_index(drop=True, inplace=True)
else:
df_start=df_end.copy()
for col in df_start.columns:
df_start.rename(columns={col: col.replace("end", "start")}, inplace=True)
vessel_last_segment = pd.DataFrame()
if last_segment.shape[0] > 0:
vessel_last_segment = last_segment.loc[
last_segment["vessel_id"] == vessel_id, ["mmsi", "timestamp_end", "heading_at_end", "speed_at_end",
"end_position", "excursion_id", "arrival_port_id"]]
vessel_last_segment["start_latitude"] = vessel_last_segment["end_position"].apply(lambda x: x.y)
vessel_last_segment["start_longitude"] = vessel_last_segment["end_position"].apply(lambda x: x.x)
vessel_last_segment.drop("end_position", inplace=True, axis=1)
vessel_last_segment.rename(columns={"timestamp_end": "timestamp_start",
"heading_at_end": "heading_at_start",
"speed_at_end": "speed_at_start",
}, inplace=True)

if vessel_last_segment.shape[0] > 0:
# if there's a last segment for this vessel, then it's not the first time a position for this vessel is received
is_new_vessel = False
# and it becomes the start point of the first new segment
df_start.loc[-1] = vessel_last_segment.iloc[0]
df_start.sort_index(inplace=True)
df_start.reset_index(drop=True, inplace=True)
# checks if the excursion of the last segment is closed or not
if vessel_last_segment["arrival_port_id"].iloc[0] >= 0:
open_ongoing_excursion = False
# concat start and end point together
df = pd.concat([df_start, df_end], axis=1)
# removing segment with same timestamp_start and timestamp_end (no update)
df = df[df["timestamp_start"] != df["timestamp_end"]].copy()
# reseting index
df.reset_index(inplace=True, drop=True)
if (df.shape[0] > 0):
# calculate distance
def get_distance_in_miles(x) -> float:
p1 = (x.start_latitude, x.start_longitude)
p2 = (x.end_latitude, x.end_longitude)
return distance.distance(p1, p2).miles

df["distance"] = df.apply(get_distance_in_miles, axis=1)
print(df)
else:
open_ongoing_excursion = True
ongoing_excursion_id = int(vessel_last_segment["excursion_id"].iloc[0])

else:
#df_start=df_end.copy()
vessel_last_segment = pd.DataFrame()
if last_segment.shape[0] > 0:
vessel_last_segment = last_segment.loc[
last_segment["vessel_id"] == vessel_id, ["mmsi", "timestamp_end", "heading_at_end", "speed_at_end",
"end_position", "excursion_id", "arrival_port_id"]]
vessel_last_segment["start_latitude"] = vessel_last_segment["end_position"].apply(lambda x: x.y)
vessel_last_segment["start_longitude"] = vessel_last_segment["end_position"].apply(lambda x: x.x)
vessel_last_segment.drop("end_position", inplace=True, axis=1)
vessel_last_segment.rename(columns={"timestamp_end": "timestamp_start",
"heading_at_end": "heading_at_start",
"speed_at_end": "speed_at_start",
}, inplace=True)
if vessel_last_segment.shape[0] > 0:
# if there's a last segment for this vessel, then it's not the first time a position for this vessel is received
is_new_vessel = False
df_start= vessel_last_segment
df_start.reset_index(drop=True, inplace=True)
# checks if the excursion of the last segment is closed or not
if vessel_last_segment["arrival_port_id"].iloc[0] >= 0:
open_ongoing_excursion = False
else:
open_ongoing_excursion = True
ongoing_excursion_id = int(vessel_last_segment["excursion_id"].iloc[0])
# if there's no last segment for this vessel, then it's the first time a position for this vessel is received
is_new_vessel = True
# so we duplicate the starting point to have the first segment while setting it up 1s behind in time (so timestamp_start != timestamp_end)
df_start.loc[-1] = df_start.loc[0]
df_start["timestamp_start"].iloc[-1] += timedelta(0, -1)
df_start.sort_index(inplace=True)
df_start.reset_index(drop=True, inplace=True)
open_ongoing_excursion = False

# concat start and end point together
df = pd.concat([df_start, df_end], axis=1)

# removing segment with same timestamp_start and timestamp_end (no update)
df = df[df["timestamp_start"] != df["timestamp_end"]].copy()
# reseting index
df.reset_index(inplace=True, drop=True)
if (df.shape[0] > 0):
# calculate distance
def get_distance_in_miles(x) -> float:
p1 = (x.start_latitude, x.start_longitude)
p2 = (x.end_latitude, x.end_longitude)
return distance.distance(p1, p2).miles

else:
# if there's no last segment for this vessel, then it's the first time a position for this vessel is received
is_new_vessel = True
# so we duplicate the starting point to have the first segment while setting it up 1s behind in time (so timestamp_start != timestamp_end)
df_start = df_end.copy()
for col in df_start.columns:
df_start.rename(columns={col: col.replace("end", "start")}, inplace=True)
df_start["timestamp_start"] += timedelta(0, -1)
df_start.sort_index(inplace=True)
df_start.reset_index(drop=True, inplace=True)
open_ongoing_excursion = False
# concat start and end point together
df = pd.concat([df_start, df_end], axis=1)
# removing segment with same timestamp_start and timestamp_end (no update)
df = df[df["timestamp_start"] != df["timestamp_end"]].copy()
# reseting index
df.reset_index(inplace=True, drop=True)
#print(df)

if (df.shape[0] > 0):
# calculate distance
def get_distance_in_miles(x) -> float:
p1 = (x.start_latitude, x.start_longitude)
p2 = (x.end_latitude, x.end_longitude)
return distance.distance(p1, p2).miles

df["distance"] = df.apply(get_distance_in_miles, axis=1)

# calculate duration in seconds
def get_duration(x) -> float:
return (x.timestamp_end - x.timestamp_start).total_seconds()

df["segment_duration"] = df.apply(get_duration, axis=1)

# set default type as AT_SEA
df["type"] = "AT_SEA"

# set type as default_ais for segment with duration > 35 min
df.loc[df["segment_duration"] >= 2100, "type"] = "DEFAULT_AIS"

# calculate average speed in knot
df["average_speed"] = df["distance"] / (df["segment_duration"] / 3600)

# set last_vessel_segment
df["last_vessel_segment"] = 0
if len(df) >1 :
df["last_vessel_segment"].iloc[-1] = 1
else :
df["last_vessel_segment"] = 1
df["distance"] = df.apply(get_distance_in_miles, axis=1)

# calculate duration in seconds
def get_duration(x) -> float:
return (x.timestamp_end - x.timestamp_start).total_seconds()

df["segment_duration"] = df.apply(get_duration, axis=1)

# set default type as AT_SEA
df["type"] = "AT_SEA"

# set type as default_ais for segment with duration > 35 min
df.loc[df["segment_duration"] >= 2100, "type"] = "DEFAULT_AIS"

# calculate average speed in knot
df["average_speed"] = df["distance"] / (df["segment_duration"] / 3600)

# set last_vessel_segment
df["last_vessel_segment"] = 0
df["last_vessel_segment"].iloc[-1] = 1

# check if segment ends in a port (only for segment with average_speed < maximal_speed_to_check_if_in_port or with type 'DEFAULT_AIS')
def get_port(x, session):
Expand Down

0 comments on commit bfb25cc

Please sign in to comment.